Skip to main navigation
Skip to search
Skip to main content
Illinois Experts Home
LOGIN & Help
Link opens in a new tab
Search content at Illinois Experts
Home
Profiles
Research units
Research & Scholarship
Datasets
Honors
Press/Media
Activities
Optimizing the Collaboration Structure in Cross-Silo Federated Learning
Wenxuan Bao
,
Haohan Wang
, Jun Wu
,
Jingrui He
School of Information Sciences
Carl R. Woese Institute for Genomic Biology
National Center for Supercomputing Applications (NCSA)
Siebel School of Computing and Data Science
Informatics
Research output
:
Contribution to journal
›
Conference article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Optimizing the Collaboration Structure in Cross-Silo Federated Learning'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Federated Learning
100%
Cross-silo Federated Learning
100%
Collaboration Structure
100%
Negative Transfer
75%
Learning Algorithm
50%
Non-overlapping
25%
Similarity Data
25%
Distribution Data
25%
Data Distribution
25%
Training Data
25%
Data Quantity
25%
Learning Model
25%
Distribution Distance
25%
Transfer Problem
25%
Machine Learning Models
25%
Local Data
25%
Multiple Clients
25%
Dataset Model
25%
Federated Learning System
25%
Clustered Federated Learning
25%
Overlapping Coalitions
25%
Non-IIDness
25%
Computer Science
Federated Learning
100%
Learning Algorithm
28%
Data Distribution
14%
Training Data
14%
Learning Framework
14%
Multiple Client
14%
Machine Learning
14%
Learning System
14%